Comment by akiselev

> People make mistakes, but people understand. Therefore, the existence of mistakes do not unilaterally discount understanding.

I'm not claiming people don't make mistakes or that an algorithm has to be perfect, I'm claiming the algorithms makes the same mistakes that people do when they're clearly don't understand something but try to cover it up with basic word association.

> You have to do actual argumentative work to demonstrate the system that shows occasions of model-based reasoning is not in fact doing model-based reasoning.

The burden of proof is on you. I can prove beyond a shadow of a doubt that a neural network is a gigantic algebraic function. You have to provide convincing evidence that it actually "understands" or has anything resembling what humans would call a "model of the world."

> All else being equal, a single (convincing) example of model-based reasoning is enough to demonstrate the existence claim.

Might as well have a quadrillion monkeys banging on type writers. As long as one of them manages to output Shakespeare's Othello, they must be as smart as humans, right? That's just cherry picking to support your preexisting conclusion.

> You have to provide an actual argument to undermine the value of the example by examples of unrelated failures.

See above. The burden of proof is on you.

For what it's worth, my mind has been blown away over the progress we've seen in the last few months and I'm very bullish on AI. I've been regularly using Replicate and OpenAI for both business and pleasur and my conclusion isn't that computers are becoming "smart" but that Brooks-Moravec-Minksy were right: https://en.wikipedia.org/wiki/Moravec%27s_paradox